Image-to-Image Translation with Conditional Adversarial Networks論文閱讀分享(pix2pix)
一.簡介 1.1研究的主要內容 本文主要研究CGANS（條件對生成抗網絡）作爲圖像到圖像轉換問題的通用解決方案，提出了pix2pix軟件，並且證明了該方法可有效地從標籤圖合成照片，從邊緣圖重建對象以及爲圖像着色等任務。 這個圖片是展示了一些圖像到圖像轉換的結果 1.2創新點 1.證明在各種問題上，conditional GAN都能產生合理的結果。 2.提出一個足以取得良好結果的簡單框架，並分析幾種
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相關文章
- 1. pix2pix（2017）：Image-to-Image Translation with Conditional Adversarial Networks
- 2. pix2pix Image-to-Image Translation with Conditional Adversarial Networks筆記及代碼實現
- 3. (Pixel2PixelGANs)Image-to-Image translation with conditional adversarial networks
- 4. Image-to-Image Translation with Conditional Adversarial Networks
- 5. Image-to-Image Translation with Conditional Adversarial Networks筆記
- 6. Image-to-Image Translation with Conditional Adversarial NetWorks 翻譯
- 7. 【翻譯】Image-to-Image Translation with Conditional Adversarial Networks
- 8. 論文閱讀：pix2pix and CycleGAN
- 9. 《Image-to-Image Translation with Conditional Adversarial Networks》論文總結
- 10. 《Image-to-Image Translation with Conditional Adversarial Networks》論文筆記